Update app.py

app.py

@@ -1,6 +1,7 @@
 import os
 import streamlit as st
 from tariff_scraper import fetch_tariff_data, save_tariff_data
+import pandas as pd
 
 # Predefined appliance list with typical loads in watts
 APPLIANCE_OPTIONS = {
@@ -59,10 +60,15 @@ if st.sidebar.button("Fetch Tariff"):
         if load_type in tariff_data:
             df = tariff_data[load_type]
             if "Variable Rs/kWh" in df.columns:
-                st.session_state.tariff_rate = float(df["Variable Rs/kWh"].iloc[0])
-                st.sidebar.success(f"Tariff fetched for {load_type}: {st.session_state.tariff_rate} PKR/unit")
+                # Filter numeric values only
+                df_numeric = df[pd.to_numeric(df["Variable Rs/kWh"], errors="coerce").notnull()]
+                if not df_numeric.empty:
+                    st.session_state.tariff_rate = float(df_numeric["Variable Rs/kWh"].iloc[0])
+                    st.sidebar.success(f"Tariff fetched for {load_type}: {st.session_state.tariff_rate} PKR/unit")
+                else:
+                    st.sidebar.warning(f"No numeric tariff rates found for {load_type}.")
             else:
-                st.sidebar.error(f"Variable Rs/kWh not found in {load_type}.")
+                st.sidebar.error(f"Variable Rs/kWh column not found in {load_type}.")
         else:
             st.sidebar.warning(f"No data available for {load_type}.")
     except Exception as e: